Abstract

BackgroundDe novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. In practice, efficiency is often a primary concern and favors using a more efficient assembler like SOAPdenovo2. Yet SOAPdenovo2, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). Assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are more favorable for longer reads.MethodsThis paper shows a new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.ResultsExperiments on two bacteria and four human datasets shows the advantage of BASE in both contig quality and speed in dealing with longer reads. In the experiment on bacteria, two datasets with read length of 100 bp and 250 bp were used.. Especially for the 250 bp dataset, BASE gives much better quality than SOAPdenovo2 and SGA and is simlilar to SPAdes. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. BASE and Soapdenov2 are further compared using human datasets with read length 100 bp, 150 bp and 250 bp. BASE shows a higher N50 for all datasets, while the improvement becomes more significant when read length reaches 250 bp. Besides, BASE is more-meory efficent than SOAPdenovo2 when sequencing data with error rate.ConclusionsBASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

Highlights

  • De novo genome assembly using NGS data remains a computation-intensive task especially for large genomes

  • Most state-of-the-art short read assemblers such as SOAPdenovo2 [2] and ALLPATHS-LG [3] are based on de Bruijn graph (DBG)

  • Datasets We compared the assembly performance based on several sets of real data, including two bacterial Staphylococcus aureusMW2 240X HiSeq 100 bp reads (SRR857914) [14], V. parahaemolyticus 240X MiSeq 250 bp reads (DRX016227) [15], and four human sequencing data sets including YH Solexa 100 bp reads [2], YH HiSeq 150 bp reads (BGI), NA12878D HiSeq X Ten 150 bp data (DNAnexus.com) and NA12878 HiSeq 250 bp data (SRR891258, SRR891259)

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Summary

Introduction

De novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. SOAPdenovo, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). The more recent NGS technologies have gradually increase the read length beyond 100 bp (e.g., 150 bp from HiSeq and 250 - 400 bp from MiSeq), yet existing efficient assemblers do not have much improvement regarding accuracy, and it remains challenge how to take better advantage of longer NGS reads to assemble genomes in a fast and accurate manner. Most state-of-the-art short read assemblers such as SOAPdenovo2 [2] and ALLPATHS-LG [3] are based on de Bruijn graph (DBG). Reads are chopped into a sequence of overlapping k-mers such that two adjacent k-mers have k-1 bases in common.

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